Modern technology now allows the analysis of immune responses and host-pathogen interactions at a global level, across scales ranging from intracellular signaling networks, to individual cell behavior, to the functioning of a tissue, organ, and even the whole organism. The challenge is not only to collect the large amounts of data such methods permit, but also to organize the information in a manner that enhances our understanding of how the immune system operates or pathogens affect their hosts. Quantitative computer simulations are gaining importance as valuable tools for probing the limits of our understanding of cellular behavior. A major roadblock on the way to computational modeling in cell biology has been that the translation of qualitative biological models into computational models required the intervention of engineers/mathematicians as interfaces between biological hypotheses and their theoretical and computational representations. The software being developed by the computational biology group of the PSIIM eliminates the necessity of having this translation done by a person and thereby reduces the risk of oversimplification of biological mechanisms or the loss of important details in the course of translation by a non-biologist. The software offers an intuitive graphical interface combined with state-of-the-art simulation technology. One focus of our work in 2008/2009 has been to develop the technology that makes it possible to create computer simulations that combine detailed biochemical representation of cellular signaling processes with the spatial resolution necessary to reproduce the effects of localized recruitment and organization of signaling components. Another focus of activity has been the creation of a database and database interface system that couples the computational models to experimental data and externally generated proteomic information. Finally, efficient stochastic simulation capabilities and the technology to simulate morphological cellular plasticity are currently being added to the softwares algorithms.